1. Field of the Invention
The present invention relates to a pixel data selection device for motion compensated interpolation and a method thereof, and more particularly, to a pixel data selection device and method in a video signal conversion.
2. Description of the Related Art
A frame rate conversion (FRC) relates to a conversion of the number of frame outputs per second. A frame rate is generally expressed as a unit of ‘Hz’. The frame rate conversion is required in different frame rates of video signals. For example, when one wants to watch a film with a 24 Hz frame rate in a TV screen with a 30 Hz frame rate, the 24 Hz frame rate of the film has to be converted to the 30 Hz frame rate of the TV screen by frame repetition and 3-2 pull-down methods.
The frame rate conversion includes an up-conversion and a down-conversion to increase and decrease the frame rate, respectively. In the down-conversion, aliasing generated during down-sampling of the video signals can be easily prevented by using a low-frequency filtering and sampling. In the up-conversion, however, a nonexistent frame has to be constructed in a temporal axis, and the aliasing generated during compensation of the non-existent frame is hardly controllable since there is no limit in determining a bandwidth of an input video signal. In addition, excessive high frequency components on a spatial axis, or excessive motions on the temporal axis further deteriorate an interpolation efficiency of the non-existent frame.
A conventional FRC algorithm is divided into a motion compensation type and a non-motion compensation type according to whether the algorithm uses motion information among frames during interpolation. The non-motion compensation type of the FRC algorithm includes the frame repetition method, a linear or non-linear time/space filter method and a simple motion interpolation method using a motion detection method in a local motion area.
The frame repetition method simply repeats a preceding frame. In other words, the frame repetition method does not use the motion information. The frame repetition method is one of conventional methods to be implemented in a hardware level. However, when one frame is converted into another frame with a different frame rate, an annoying view like motion jitter or blurring occurs.
In order to overcome the above problems, a time/space filter interpolation method has been suggested. In the time/space filter interpolation method, a time/space filter is used to filter neighboring frames of an interpolated frame. This method, however, cannot prevent the aliasing during the interpolation. If an input image contains excessive high frequency components on a spatial axis, the blurring occurs in the interpolated frame.
The motion interpolation method is based on both a motion-compensated interpolation (MCI) and a linear interpolation. This method detects a motion in a local area and simplifies computational complexities for motion compensation by applying the detected motion to the linear interpolation of adjacent frames. More specifically, the motion interpolation method performs the interpolation by using a median filter eliminating irregular motion vectors detected from a motion detecting process, and averaging the motion vectors along motion trajectories.
FIG. 1 is a block diagram showing a general structure of a conventional frame rate converting apparatus, and FIG. 2 is a view showing an image segmentation used in the conventional frame rate converting apparatus of FIG. 1.
Referring to FIG. 1, the conventional frame rate converting apparatus 100 includes an image segmentation portion 110, a motion estimation portion 120, a motion vector refinement portion 130 and a motion compensated-interpolation (MCI) portion 140. As shown in FIG. 2, the image segmentation portion 100 divides an image into a changed region and an unchanged region. The changed region is again divided into a covered region and an uncovered region, a stationary background region and a moving object region for more efficient motion estimation.
The motion estimation portion 120 estimates the motion in a unit of pixel or block. A motion vector of a block is generated by a block matching algorithm that is generally used in video coding. The block matching algorithm obtains the motion vector for each block based on an assumption that pixels within a certain sized block are moved at a constant rate, i.e., the pixels are moved without enlargement or reduction. The motion estimation in the pixel unit is performed in order to obtain the motion vector closer to a true image. For the motion estimation in a pixel unit, first, based on the assumption that the pixels within the block have a uniform motion, the motion vector of the block unit is obtained. Then, based on the motion vector of the block unit, a motion vector of each pixel of the block is obtained.
When a proper motion vector is not obtained, however, a visual effect would be less than when the motion information is not used at all. Accordingly, the motion vector refinement portion 130 refines the improper motion vector that is obtained from the motion estimation portion 120. The MCI portion 140 obtains the motion vector in a forward direction of the preceding and following frames of an image for interpolation. Then, by using the estimated motion vector, the image for interpolation is recognized according to the regions divided by the image segmentation portion 110. In other words, the MCI portion 140 compensates motions by using motion information between adjacent frames like the preceding and following frames of a certain image of a current frame to be interpolated.
And sometimes, an inaccurate result is obtained from the motion estimation due to the estimated motion vector that is different from a true motion vector. When there is inaccurate motion estimation by the MCI portion 140, blocking artifacts occur in interpolated images. Accordingly, after-process methods like an overlapped block motion compensation (OBMC) method are used to remove the blocking artifacts. The OBMC method, however, is only effective when the artifacts of pixel data change edges of the block irregularly. In a format conversion like deinterlacing and the frame/field rate conversion (FRC), the after-process methods such as an OBMC method are not effective in blocking artifacts where the pixel data within the interpolated block is very quite different from that of the adjacent blocks.